| Credit: | 6 |
|---|---|
| Status: | CSF - elective EEI and EP - elective English ET - elective F,FM and B - elective Finanční trhy a datová analýza - mandatory Masters - all MEF - elective MFDA - core Semester - summer |
| Course supervisors: | prof. Roman Horváth Ph.D. |
| Course homepage: | JEM116 |
| Literature: | |
| Description: | Applied Econometrics Organization: Summer semester, every Thursday, 5PM – lecture, 6.20PM – seminar 1, 11:00AM - seminar 2 Room 314 (for the lectures)/016 (for the seminars) IES, Opletalova 26, Prague 1 Lecturers: Jozef Barunik (barunik@fsv.cuni.cz) Jaromir Baxa (jaromir.baxa@fsv.cuni.cz) Kristyna Brunova (kristyna.brunova@fsv.cuni.cz) Roman Horvath (roman.horvath@fsv.cuni.cz) Jirka Kukacka (jiri.kukacka@fsv.cuni.cz) Matej Nevrla (matej.nevrla@fsv.cuni.cz) The course concentrates on the practical use of econometric methods, reviewing the relevant methodology, its use, and the possible alternative modeling approaches. The lectures are supplemented by computer classes, where students can gain hands-on experience in applied econometric analysis. During the course we will especially focus on time series techniques applied to forecasting asset volatility, modeling inflation, exchange rate volatility and other topics that you may regularly encounter in economic and financial literature. The course focuses on following topics in econometrics: OLS, IV, ARIMA, GARCH, VAR, cointegration, non-linear model and limited dependent variable. The course is especially suited for students undertaking empirical exercise in writing their M.A. thesis. We follow most closely: Brooks, Chris, Introductory Econometrics for Finance. Third Edition. Cambridge Univeristy Press. Selected other textbooks on applied econometrics: Asteriou, D., Hall, S. "Applied Econometrics", 3rd edition, 2015 Enders, W.: “Applied Econometric Time Series“, 2nd edition, 2003 Harris, R. and R. Sollis: "Applied Time Series Modelling and Foecasting", 2003 Stewart, K. G.: "Introduction to Applied Econometrics", 2005 Verbeek, M.: “A Guide to Modern Econometrics”, 2nd edition, 2004 Kratzig, M. and H. Lutkepohl ,“Applied Time Series Econometrics”, 2004 Kocenda, E. and A. Cerny, "Elements of Time Series Econometrics: An Applied Approach", 2007, Karolinum Press Assessment: - written exam at the end of semester (60%) - term paper (40%) Term paper – in general, student may choose any topic after consulting the lecturer or may accept a topic and data that the lecturer will propose. Some examples of topics of individual assignment from the previous years: The effect of spot position of exchange rate within the fluctuation band on its volatility: Evidence from Hungary, PX-50 stock market returns and volatility modeling, Daily effects of volatility of stock markets in central Europe. 1. Introduction Lecture Notes 2. OLS,TSLS, IV Lecture Notes Angrist and Krueger (2001): Instrumental Variables and the Search for Identification, Journal of Economic Perspectives, pp.69-85. Hausman (2001): Mismeasured Variables in Econometric Analysis: Problems from the Right and Problems from the Left, Journal of Economic Perspectives, pp. 57-67. Horvath, R. (2005): Exchange Rate Variability, Pressures and Optimum Currency Area Criteria: Some Empirical Evidence from 1990s, Applied Economics Letters, pp. 919-922. 3. Introduction to Time Series Lecture Notes 4. ARIMA Modeling Lecture Notes 5. GARCH (2 lectures) Lecture Notes Choudhry, T. (2000): Day of the week effect in emerging Asian stock markets: Evidence from the GARCH model, Applied Financial Economics, 235-242. Engle, R. (2001): GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics, Journal of Economic Perspectives, pp. 157-168. Engle, R. (2003): Risk and Volatility: Econometric Models and Financial Practice, Nobel lecture, December 8, 2003, downloadable from http://nobelprize.org/nobel_prizes/economics/laureates/2003/engle-lecture.pdf Kocenda, E. (1998): Exchange Rate in Transition (chapters 2-3), CERGE-EI, downloadable from http://www.cerge-ei.cz/pdf/books/exchange_rate.pdf. Fidrmuc, J. and R. Horvath (2008): Volatility of Exchange Rates in Selected EU New Members: Evidence from Daily Data, Economic Systems, pp. 103-118. The Royal Swedish Academy of Sciences (2003): Time Series Econometrics: Cointegration and Autoregressive Conditional Heteroscedasticity, downloadable from http://www.kva.se/KVA_Root/files/newspics/DOC_2003108143127_50163615451_ecoadv03.pdf 6. Introduction to Cointegration Lecture Notes The Royal Swedish Academy of Sciences (2003): Time Series Econometrics: Cointegration and Autoregressive Conditional Heteroscedasticity, downloadable from http://www.kva.se/KVA_Root/files/newspics/DOC_2003108143127_50163615451_ecoadv03.pdf Granger, C. W.J. (2003): Time Series, Cointegration and Applications, Nobel lecture, December 8, 2003, downloadable from http://repositories.cdlib.org/cgi/viewcontent.cgi?article=1019&context=ucsdecon 7. Vector Autoregression (2 lectures) Lecture Notes Stock and Watson (2001): Vector Autoregressions, Journal of Economic Perspectives, pp. 101-115 Ivanov and Kilian (2005): A Practitioner Guide to Lag Order Selection for VAR Impulse Response Analysis, Studies in Non-linear Dynamics & Econometrics, Article 2. Borys Morgese, M., Franta, M. and R. Horvath (2009): The Effects of Monetary Policy in the Czech Republic: An Empirical Study, Empirica, 419-443. Horvath, R. and M. Rusnak (2009): How Important Are Foreign Shocks in Small Open Economy? The Case of Slovakia, Global Economy Journal, 1, Article 5. 8. Limited Dependent Variables and their Use in Finance (Credit scoring, Ratings, etc.) Lecture notes Poon, W. (2003): Are Unsolicited Credit Ratings Biased Downward? Journal of Banking and Finance, 27(4), 593-614. 9. Non-linear models, structural breaks Lecture notes Gregoriou, A. and Kontonikas, A. (2009): Modeling the Behaviour of Inflation Deviations from the Target, Economic Modelling, 26, 90-95. 10. Introduction to Time Series Filters Lecture notes Mandatory are only lecture notes. Other readings are recommended. For running demonstrations you will need the Mathematica Player, which can be freely downloaded here: http://www.wolfram.com/products/player/. Save them as *.nbp and open with Mathematica Player. Software - R For your term paper you are free to use econometric software you like. During the classes, we are going to use JMulTi (time series econometric software). It is free to download from www.jmulti.com and very easy to use. There is online help or you can download all online-help chapters in pdf. You can also download Gretl for free from the web at http://gretl.sourceforge.net/. There is a companion e-book at http://www.learneconometrics.com/gretl/ebook.pdf. You may also read the textbook that uses gretl extensively: Hill, C.R., Griffiths, W.E. and Lim, G.C.: "Principles of Econometrics", Third Edition, 2008, Wiley Office hours By appointment, send us e-mail or contact us after the lecture. |
